The pandemic has changed the world and has impacted many companies on doing business. Prior to pandemic, remote work was still a thing, but many organizations had zero tolerance or policy for remote work. As the year pass, organization have seen the benefits and challenges with remote working. This has led may companies to go 100% digital and accelerated digital transformation causing everyone to start porting things over to apps and software as the only wat to interact with customers. This is also leading improvement and new development of applications and rapid changes to meet customer demands. These dynamic changes have caught organization unprepared. To keep up with the changes and provide quality product these organizations are relying on their software testing capabilities. The new shift in software testing has embark new testing trends and adoption of new technology.
Increase use of automation:
There is no doubt automation testing has played an important role in the SDLC process with faster development process. Post COVID 19, automation testing approach will change with high demand of Performance and load testing and security testing of applications. To perform efficient testing there will be needed to create proper test environment to test with appropriate data and servers to handle the load of testers using these servers. SAAS, cloud based, servers will be more effective for testing teams to access test data from their remote location.
AI in Software Testing:
The adoption of AI- based technology has become a key goal for my companies and implementing to all the aspects of SDLC including software testing. AI-based testing platforms help companies reduce the complexities in testing Artificial Intelligence (AI) and machine learning (ML) implementations. Many companies are focusing on building AI capabilities to enhance their software testing efficiency in all phases of the QA lifecycle. AI and machine learning-based QA is powered by supervised and unsupervised methods to unlock the power of data, test artifacts, project documentation, defect logs, test results and production incidents. AI helps in optimizing the testing part and even allows for predicting failure points reducing any blocker during the testing phase. QA teams can leverage AI and ML to improve their automation testing strategies and can discover and prioritize the scope for additional automated testing that can help in backlogs and staying on top of recurrent releases. Al can optimize test suited after identifying unneeded test cases and ensuring optimal test coverage comparing with requirement traceability matrix (RTM).
Testing in agile environment:
Prior to covid, many organizations had adopted agile methodology. When covid hit many organizations had to make dynamic implementation changes of their applications. They benefited from agile based testing that helped them achieve their development goals. Those organizations that were hybrid or in waterfall module were forced to adopted agile methodology. Post covid this will be a norm for many organizations to have all their projects in agile. The benefit of agile testing is testing is readily available with written test scripts, test cases etc. Regardless of who build the tests they are readily available to be run at any time as part of the CI/CD process. Automate tests developed by testers can be executed by developers or by the CI engine as part of the build verification process. With the help of test automation high test coverage in every sprint can be achieved that gives an instant feedback of development. Agile is a constant procedure of development and testing and it facilitate top quality products at a fast rate. Agile has been a big trend and post covid world many organizations are revisiting and adopting new agile testing methods, such as shift- left testing. The sudden shift to remote working was unexpected and all the organizations had to adopted it. After months of remote working there are improvements and lessons learned that can be implemented to agile environment. Because of changes and going digital there were frequent release and taking longer sprint time and in some cases a lot of backlog and resources were burnout. As we get into post covid, many agile teams have realized to have a good sprint planning, daily scrum, sprint review and sprint retrospective to reduce spring backlog and delays for a successful agile sprint. Getting back to the office is not very promising; enhancing remote work culture and keeping the team engaged for a successful agile team.
Big Data Testing
The adopting of Big data programs helps in data analytics solution on a large scale. Therefore, they require a robust strategy for E2E testing in optimum test environment for a successful implementation. Big Data testing offering of E2E testing is from data analytics testing to data acquisition testing. Companies use robust tools and Big Data utilities to automate Big Data validation. Applications that involve vast volumes of consumer data need to be tested and analyzed. Internet of Things (IoT) is a fast-growing concept in the technology, and it is expected to grow more as it will accept 5G standard and paved the way for added varied data volume generation which created a need of big data testing for instance for big e-commerce companies like Amazon. Big data testing confidently impacts enterprises’ capability to validate info, create data-driven verdicts, and improve market strategizing and targeting.
Accessibility testing is a subset of usability testing. It is needed to assure the application being tested to be used for people with disabilities. The need for accessibility testing will be required more for individual who have disabilities and are relying on digital services for more than ever before for everyday activities such as banking, shopping, healthcare etc. Starting of pandemic use of education and business app have doubled. Prediction is after post covid the use of these apps will not decrease and they need to be accessible and easy to use for people of disability. Therefore, accessibility testing will be a key in the QA life cycle.
Cloud based Test Management Tools to Manage Remote Teams:
When coordinating and managing remote testing teams it can be extremely daunting and having everyone 100% remote brings its own challenges. When software testing gets disconnected from other development process, its outcomes include slower releases and project failures. Hence, it is extremely important to ensure that tests are run effectively and that defects are also being addressed in a timely manner. Therefore, it is important to implement Test Management tools to handle remote teams and monitor day to day progress. These Test management tools, such as JIRA, HP ALM etc. should not be limited to testing teams but implement across the board with dev team, Business, and stakeholders. This keeps the whole project on track and easy to monitor test execution, defect triaging and test schedule. The use of cloud based and DevOps tools such as Azure have significantly increased. Many organizations are looking into other open-source cloud-based tools and introducing them to their teams. These do not only benefit the test team but also overall projects. There are codeless automated testing tools that are build up of AI and have cloud-based technology that accelerate testing.
InfoSec/Cyber Security testing:
During pandemic, there was increase of cyber-attacks and higher cybersecurity threats. The growing technology sectors and number of new implementations and expansion of digital platforms has made cybersecurity testing a top priority. Post covid, security tests will be the key emerging trend in software testing. That will help in increased awareness of any vulnerability threats, increase product and software security, executing security checks earlier in the SDLC. Since many organizations are now digital there is a huge risk of data breach especially post covid where sensitive data is being shared for day-to-day activities for banking, shopping, education etc. Regardless the size of organization, they are al targets. The common kind of cyber attacks are observing an uptick are ransomware, harsh attacks, and island hopping. The Ransomware attack are criminals encrypt files and then claim a ransom to bring back access; this attach has jumped to 90 percent during pandemic. Destructive hits or attacks wherein networks or data are destroyed are up 102 percent. Whereas Island hopping (where criminals take over the digital revolution efforts of organizations) utilizes their networks to attack partners and users is up by 33 percent. Cybersecurity testing should be an ongoing process before and after the application is in production to prevent any attacks and spot areas susceptible to cyber-attacks or threats. Regular pen test contributes a good reputation and help win greater trust from the customer.